Sr. Applied Scientist, Personal Robotics Group

Amazon • Sunnyvale, CA

1d

About The Position

Join the Personal Robotics Group at Amazon, where you'll help pioneer intelligent robotic products that deliver meaningful customer experiences. As a Senior Applied Scientist, you'll drive technical excellence in robotic task planning, developing and improving algorithms that enable robots to learn and execute complex tasks in dynamic real-world environments, while establishing evaluation and benchmarking methodology to measure system performance. In this role, you will combine hands-on technical work with scientific rigor, researching and developing novel approaches to task planning and understanding, improving models to enhance performance, and designing experiments and benchmarks that drive measurable progress. You'll leverage Amazon's computational resources and robotics infrastructure to tackle ambitious challenges in areas such as task planning, task understanding, reasoning, and human-robot interaction. The Personal Robotics Group is pioneering intelligent robotic products that deliver meaningful customer experiences. We're building the next generation of robotic systems that will redefine how customers interact with technology. This is a unique opportunity to shape the future of personal robotics working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, task planning, and human-robot interaction. Join us if you're passionate about creating the future of personal robotics, solving complex challenges at the intersection of hardware and software, and seeing your innovation deliver transformative customer experiences.

Requirements

• PhD, or Master's degree and 6+ years of applied research experience
• 3+ years of industry or academic research experience
• Experience with programming languages such as Python, Java, C++
• Experience designing experiments with quantitative evaluation and benchmarking methodology for AI or robotics systems
• Experience with LLMs, VLMs, or large multimodal models and their evaluation challenges
• Experience with robotics task planning, reasoning, or complex task understanding
• Strong publication record at major conferences (RSS, CoRL, ICRA, IROS, HRI, NeurIPS, ICML, or similar)
• Experience building evaluation pipelines or benchmarks for robotics or AI systems
• Experience with model fine-tuning and training for robotics applications
• Experience with complex task decomposition and multi-modal task understanding
• Experience with simulation environments for robotics
• The ability to work with minimal guidance, be proactive, deal with ambiguity, and thrive with quickly evolving goals
• Demonstrated experimental mindset with a track record of hypothesis-driven research
• Experience bridging research with practical engineering implementation in robotics systems

Responsibilities

• Research and develop novel approaches to robotic task planning, task understanding, and reasoning to improve system performance
• Design and implement evaluation frameworks and benchmarks for robotic planning systems, driving measurable improvements
• Explore and fine-tune models to enhance robot capabilities across diverse tasks and environments
• Build and maintain datasets and data collection pipelines for training and evaluating models
• Define quantitative metrics and success criteria that connect evaluation results to real-world robot performance
• Collaborate with engineering teams to integrate research findings and evaluation into development workflows
• Partner with cross-functional teams to ensure holistic improvement of robot capabilities
• Stay current with the latest advancements in robotics, task planning, and AI research
• Research and prototype new approaches to improve task planning and understanding capabilities
• Design and run experiments to identify limitations of current approaches, documenting findings and proposing improvements
• Fine-tune and iterate on models to improve performance across diverse scenarios
• Build and iterate on evaluation pipelines that measure system quality and reliability

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree